Integrating Skills for the Internet of Things
Software may be eating the world, as Marc Andreessen says, but it is doing so by embedding itself into things and then connecting them into larger systems. The handle for this massive trend is the Internet of Things or IoT. Companies of all types need to reskill in order to be part of this. Companies that fail to do so will fade away.
What kind of companies should care about the Internet of Things? Anyone involved in designing infrastructure to begin with. As we saw with The Living Bridge, any major piece on infrastructure is now a system in which the sensors and actuators are as important as the fixed structures. The sensors collect data on environment and performance. The actuators, everything from traffic control systems to equipment able to reconfigure the asset, allow for adaptive response to the situation. As the Internet of Things becomes wider and more a part of our lives the social dimension also comes to the fore. Bridges, transit systems, intelligent car and bicycles, all become foci for communities that share and act on data.
Let’s look at an example. One of the fastest growing companies in Vancouver is the precision agriculture company Semios. This company is instrumenting orchards to give farmers more insight and control over their crops. By doing this, it is able to cut down on use of pesticides and reduce energy consumption. The company is getting great traction in the California almond and pistachio industries, and is also used extensively in apple orchards from the Okanagan in British Columbia, down through the Yakima valley in Washington and into Oregon. Semios provides a complex set of systems as the illustration below shows. The skills needed to bring together all of these different technologies and make them useful and meaningful for farmers is mind boggling.
To support companies like Semios and other Internet of Things vendors, we need a new, integrative, model of skill management. We need to recognize that skills connect in new and unexpected ways. A rigid approach to skill management, in which each skill has a fixed place in a larger taxonomy or competency model, just won’t work in a world where community management skills need to be connected to data collection. Both contribute to predictive analytics. Skill management is also domain driven, as we can see from Semios, where a deep knowledge of almond farming and pest behaviour is as important as technical expertise.
“Growing the company has been about growing our skills and figuring out how all of the pieces fit together. We began with pheromones and then asked how to best disperse them in orchards. This took us to weather stations as we need to know the microclimates in order to know when and how to deliver the pheromones. All of this had to be connected, so we introduced mesh networks, and by this time we were gathering enough data to start predicting pest and disease outbreaks. We now know more about what is happening in the orchards than any other system and we continue to branch out. We recently added control of irrigation and frost management systems. As we get better and better coverage, we are starting to see how what happens in one orchard impacts another; it's one big, connected ecosystem. For example, when almonds are harvested, the insects that had been living there can fly off to infect pistachios orchards several miles away!” explained Semios CEO Michael Gilbert in a recent conversation.
We now know enough to begin sketching a general skill model for the Internet of Things. The cycle of Sense—Connect—Understand—Predict— Act seems compelling. Few today would question the need to understand the domain and to engage with stakeholders. These two activities are in fact closely related. What is much harder is to understand and support the connections between these, the blue lines in the below figure.
This is what TeamFit is working on. Identifying the connections between skills and how these combine to support performance on complex projects. The concepts of Associated Skills and Complementary skills are essential here. One cannot build a skill management system for the Internet of Things, or any other cross-disciplinary work, without these two ways of connecting skills.
Associated Skills—Skills often used together by the same person. If a person has one skill they are likely to have the other. The pattern of associated skills for an individual, team and company suggest how it will approach work.
Complementary Skills—Skills frequently used together by two different people. Each skill makes the other more effective and valuable.
Join us in building a new approach to skill management. One that will make you and your projects more successful.
